Overexpression of BnaA10.WRKY75 Decreases Cadmium and Salt Tolerance via Increasing ROS Accumulation in Arabidopsis and Brassica napus L.

Soil is indispensable for agricultural production but has been seriously polluted by cadmium and salt in recent years. Many crops are suffering from this, including rapeseed, the third largest global oilseed crop. However, genes simultaneously related to both cadmium and salt stress have not been extensively reported yet. In this study, BnaA10.WRKY75 was screened from previous RNA-seq data related to cadmium and salt stress and further analyses including sequence comparison, GUS staining, transformation and qRT-PCR were conducted to confirm its function. GUS staining and qRT-PCR results indicated BnaA10.WRKY75 was induced by CdCl2 and NaCl treatment. Sequence analysis suggested BnaA10.WRKY75 belongs to Group IIc of the WRKY gene family and transient expression assay showed it was a nuclear localized transcription factor. BnaA10.WRKY75-overexpressing Arabidopsis and rapeseed plants accumulated more H2O2 and O2- and were more sensitive to CdCl2 and NaCl treatment compared with untransformed plants, which may be caused by the downregulation of BnaC03.CAT2. Our study reported that BnaA10.WRKY75 increases sensitivity to cadmium and salt stress by disrupting the balance of reactive oxygen species both in Arabidopsis and rapeseed. The results support the further understanding of the mechanisms underlying cadmium and salt tolerance and provide BnaA10.WRKY75 as a valuable gene for rapeseed abiotic stress breeding.

Enhancing climate change resilience in agricultural crops.

Climate change threatens global food and nutritional security through negative effects on crop growth and agricultural productivity. Many countries have adopted ambitious climate change mitigation and adaptation targets that will exacerbate the problem, as they require significant changes in current agri-food systems. In this review, we provide a roadmap for improved crop production that encompasses the effective transfer of current knowledge into plant breeding and crop management strategies that will underpin sustainable agriculture intensification and climate resilience. We identify the main problem areas and highlight outstanding questions and potential solutions that can be applied to mitigate the impacts of climate change on crop growth and productivity. Although translation of scientific advances into crop production lags far behind current scientific knowledge and technology, we consider that a holistic approach, combining disciplines in collaborative efforts, can drive better connections between research, policy, and the needs of society.

Genetic and molecular analysis of stem rot (Sclerotinia sclerotiorum) resistance in Brassica napus (canola type).

Identifying the molecular and genetic basis of resistance to Sclerotinia stem rot (Sclerotinia sclerotiorum) is critical for developing long-term and cost-effective management of this disease in rapeseed/canola (Brassica napus). Current cultural or chemical management options provide, at best, only partial and/or sporadic control. Towards this, a B. napus breeding population (Mystic x Rainbow), including the parents, F1, F2, BC1P1 and BC1P2, was utilized in a field study to determine the inheritance pattern of Sclerotinia stem rot resistance (based on stem lesion length, SLL). Broad sense heritability was 0.58 for SLL and 0.44 for days to flowering (DTF). There was a significant negative correlation between SLL and stem diameter (SD) (r = -0.39) and between SLL and DTF (r = -0.28), suggesting co-selection of SD and DTF traits, along with SLL, should assist in improving overall resistance. Non-additive genetic variance was evident for SLL, DTF, and SD. In a genome wide association study (GWAS), a significant quantitative trait locus (QTL) was identified for SLL. Several putative candidate marker trait associations (MTA) were located within this QTL region. Overall, this study has provided valuable new understanding of inheritance of resistance to S. sclerotiorum, and has identified QTL, MTAs and transgressive segregants with high-level resistances. Together, these will foster more rapid selection for multiple traits associated with Sclerotinia stem rot resistance, by enabling breeders to make critical choices towards selecting/developing cultivars with enhanced resistance to this devastating pathogen.

Accuracy of Selection in Early Generations of Field Pea Breeding Increases by Exploiting the Information Contained in Correlated Traits.

Accuracy of predicted breeding values (PBV) for low heritability traits may be increased in early generations by exploiting the information available in correlated traits. We compared the accuracy of PBV for 10 correlated traits with low to medium narrow-sense heritability (h2) in a genetically diverse field pea (Pisum sativum L.) population after univariate or multivariate linear mixed model (MLMM) analysis with pedigree information. In the contra-season, we crossed and selfed S1 parent plants, and in the main season we evaluated spaced plants of S0 cross progeny and S2+ (S2 or higher) self progeny of parent plants for the 10 traits. Stem strength traits included stem buckling (SB) (h2 = 0.05), compressed stem thickness (CST) (h2 = 0.12), internode length (IL) (h2 = 0.61) and angle of the main stem above horizontal at first flower (EAngle) (h2 = 0.46). Significant genetic correlations of the additive effects occurred between SB and CST (0.61), IL and EAngle (-0.90) and IL and CST (-0.36). The average accuracy of PBVs in S0 progeny increased from 0.799 to 0.841 and in S2+ progeny increased from 0.835 to 0.875 in univariate vs MLMM, respectively. An optimized mating design was constructed with optimal contribution selection based on an index of PBV for the 10 traits, and predicted genetic gain in the next cycle ranged from 1.4% (SB), 5.0% (CST), 10.5% (EAngle) and -10.5% (IL), with low achieved parental coancestry of 0.12. MLMM improved the potential genetic gain in annual cycles of early generation selection in field pea by increasing the accuracy of PBV.

Optimal Contribution Selection Improves the Rate of Genetic Gain in Grain Yield and Yield Stability in Spring Canola in Australia and Canada.

Crop breeding must achieve higher rates of genetic gain in grain yield (GY) and yield stability to meet future food demands in a changing climate. Optimal contributions selection (OCS) based on an index of key economic traits should increase the rate of genetic gain while minimising population inbreeding. Here we apply OCS in a global spring oilseed rape (canola) breeding program during three cycles of S0,1 family selection in 2016, 2018, and 2020, with several field trials per cycle in Australia and Canada. Economic weights in the index promoted high GY, seed oil, protein in meal, and Phoma stem canker (blackleg) disease resistance while maintaining plant height, flowering time, oleic acid, and seed size and decreasing glucosinolate content. After factor analytic modelling of the genotype-by-environment interaction for the additive effects, the linear rate of genetic gain in GY across cycles was 0.059 or 0.087 t ha-1 y-1 (2.9% or 4.3% y-1) based on genotype scores for the first factor (f1) expressed in trait units or average predicted breeding values across environments, respectively. Both GY and yield stability, defined as the root-mean-square deviation from the regression line associated with f1, were predicted to improve in the next cycle with a low achieved mean parental coancestry (0.087). These methods achieved rapid genetic gain in GY and other traits and are predicted to improve yield stability across global spring canola environments.

Quantitative Trait Loci for Heat Stress Tolerance in Brassica rapa L. Are Distributed across the Genome and Occur in Diverse Genetic Groups, Flowering Phenologies and Morphotypes.

Heat stress events during flowering in Brassica crops reduce grain yield and are expected to increase in frequency due to global climate change. We evaluated heat stress tolerance and molecular genetic diversity in a global collection of Brassica rapa accessions, including leafy, rooty and oilseed morphotypes with spring, winter and semi-winter flowering phenology. Tolerance to transient daily heat stress during the early reproductive stage was assessed on 142 lines in a controlled environment. Well-watered plants of each genotype were exposed to the control (25/15 °C day/night temperatures) or heat stress (35/25 °C) treatments for 7 d from the first open flower on the main stem. Bud and leaf temperature depression, leaf conductance and chlorophyll content index were recorded during the temperature treatments. A large genetic variation for heat tolerance and sensitivity was found for above-ground biomass, whole plant seed yield and harvest index and seed yield of five pods on the main stem at maturity. Genetic diversity was assessed on 212 lines with 1602 polymorphic SNP markers with a known location in the B. rapa physical map. Phylogenetic analyses confirmed two major genetic populations: one from East and South Asia and one from Europe. Heat stress-tolerant lines were distributed across diverse geographic origins, morphotypes (leafy, rooty and oilseed) and flowering phenologies (spring, winter and semi-winter types). A genome-wide association analysis of heat stress-related yield traits revealed 57 SNPs distributed across all 10 B. rapa chromosomes, some of which were associated with potential candidate genes for heat stress tolerance.

A chickpea genetic variation map based on the sequencing of 3,366 genomes.

Zero hunger and good health could be realized by 2030 through effective conservation, characterization and utilization of germplasm resources1. So far, few chickpea (Cicer arietinum) germplasm accessions have been characterized at the genome sequence level2. Here we present a detailed map of variation in 3,171 cultivated and 195 wild accessions to provide publicly available resources for chickpea genomics research and breeding. We constructed a chickpea pan-genome to describe genomic diversity across cultivated chickpea and its wild progenitor accessions. A divergence tree using genes present in around 80% of individuals in one species allowed us to estimate the divergence of Cicer over the last 21 million years. Our analysis found chromosomal segments and genes that show signatures of selection during domestication, migration and improvement. The chromosomal locations of deleterious mutations responsible for limited genetic diversity and decreased fitness were identified in elite germplasm. We identified superior haplotypes for improvement-related traits in landraces that can be introgressed into elite breeding lines through haplotype-based breeding, and found targets for purging deleterious alleles through genomics-assisted breeding and/or gene editing. Finally, we propose three crop breeding strategies based on genomic prediction to enhance crop productivity for 16 traits while avoiding the erosion of genetic diversity through optimal contribution selection (OCS)-based pre-breeding. The predicted performance for 100-seed weight, an important yield-related trait, increased by up to 23% and 12% with OCS- and haplotype-based genomic approaches, respectively.

Multivariate genomic analysis and optimal contributions selection predicts high genetic gains in cooking time, iron, zinc, and grain yield in common beans in East Africa.

Common bean (Phaseolus vulgaris L.) is important in African diets for protein, iron (Fe), and zinc (Zn), but traditional cultivars have long cooking time (CKT), which increases the time, energy, and health costs of cooking. Genomic selection was used to predict genomic estimated breeding values (GEBV) for grain yield (GY), CKT, Fe, and Zn in an African bean panel of 358 genotypes in a two-stage analysis. In Stage 1, best linear unbiased estimates (BLUE) for each trait were obtained from 898 genotypes across 33 field trials in East Africa. In Stage 2, BLUE in a training population of 141 genotypes were used in a multivariate genomic analysis with genome-wide single nucleotide polymorphism data from the African bean panel. Moderate to high genomic heritability was found for GY (0.45 ± 0.10), CKT (0.50 ± 0.15), Fe (0.57 ± 0.12), and Zn (0.61 ± 0.13). There were significant favorable genetic correlations between Fe and Zn (0.91 ± 0.06), GY and Fe (0.66 ± 0.17), GY and Zn (0.44 ± 0.19), CKT and Fe (-0.57 ± 0.21), and CKT and Zn (-0.67 ± 0.20). Optimal contributions selection (OCS), based on economic index of weighted GEBV for each trait, was used to design crossing within four market groups relevant to East Africa. Progeny were predicted by OCS to increase in mean GY by 12.4%, decrease in mean CKT by 9.3%, and increase in mean Fe and Zn content by 6.9 and 4.6%, respectively, with low achieved coancestry of 0.032. Genomic selection with OCS will accelerate breeding of high-yielding, biofortified, and rapid cooking African common bean cultivars.

Fast-forward breeding for a food-secure world.

Crop production systems need to expand their outputs sustainably to feed a burgeoning human population. Advances in genome sequencing technologies combined with efficient trait mapping procedures accelerate the availability of beneficial alleles for breeding and research. Enhanced interoperability between different omics and phenotyping platforms, leveraged by evolving machine learning tools, will help provide mechanistic explanations for complex plant traits. Targeted and rapid assembly of beneficial alleles using optimized breeding strategies and precise genome editing techniques could deliver ideal crops for the future. Realizing desired productivity gains in the field is imperative for securing an adequate future food supply for 10 billion people.